A framework for developing and evaluating digital and public health tools

BackgroundThere is increasing interest in digital technologies to help improve children and young people’s mental health, and the evidence for the effectiveness for these approaches is rising. However, there is concern regarding levels of user engagement, uptake and adherence. Key guidance regarding digital health interventions stress the importance of early user input in the development, evaluation and implementation of technologies to help ensure they are engaging, feasible, acceptable and potentially effective. Co-design is a process of active involvement of stakeholders, requiring a change from the traditional approaches to intervention development. However, there is a lack of literature to inform the co-design of digital technologies to help child and adolescent mental health.MethodsWe reviewed the literature and practice in the co-design of digital mental health technologies with children and young people. We searched Medline, PsycInfo and Web of Science databases, guidelines, reviews and reference lists, contacted key authors for relevant studies, and extracted key themes on aspects of co-design relevant to practice. We supplemented this with case studies and methods reported by researchers working in the field.ResultsWe identified 25 original articles and 30 digital mental health technologies that were designed/developed with children and young people. The themes identified were as follows: principles of co-design (including potential stakeholders and stages of involvement), methods of involving and engaging the range of users, co-designing the prototype and the challenges of co-design.ConclusionsCo-design involves all relevant stakeholders throughout the life and research cycle of the programme. This review helps to inform practitioners and researchers interested in the development of digital health technologies for children and young people. Future work in this field will need to consider the changing face of technology, methods of engaging with the diversity in the user group, and the evaluation of the co-design process and its impact on the technology.

Has traditional medicine had its day? The need to redefine academic medicine

There are dynamic interactions between (digital) technologies and society. Digital technologies have a(re-)structuring effect on social relationships and social innovations in avariety of ways. Because of these characteristics, technological innovations affect our individual lifestyles and living environments. In particular, the development and implementation of interventions with digital (health) technologies is attracting increasing national and international attention (e.g. telematics GP consultations and app-supported patient education programs).Digital health technologies enable new forms of interaction and knowledge-based reproduction in the field of health. The integration of potential users in the development process of digital health technologies and interventions requires the discussion of new research approaches. The interests, needs, and requirements of users may influence the nonuse of digital health technologies. It is above all the successful implementation, involving potential users, that can have an influence on acceptance and integrative use in the later course of care. The discourse on the participatory development and implementation of interventions with digital health technologies in the field of digital public health presents itself as acomplex process characterized by various theoretical approaches and methodological procedures and requiring representation, evaluation, and classification.

Designing digital health applications for climate change mitigation and adaptation.

ZusammenfassungDie rasante Entwicklung neuer digitaler Technologien hat nicht nur die medizinische Praxis verändert, sondern bietet auch große Chancen und Herausforderungen für Public Health, insbesondere in Gesundheitsförderung und Prävention.Gleichzeitig ist dieses neue Feld auch gekennzeichnet durch begriffliche und konzeptuelle Unschärfen, einen bemerkenswerten Mangel an qualitativ hochwertiger Evidenz sowie eine fehlende Diskussion von unerwünschten Effekten und Begleiterscheinungen. Eine weitere Herausforderung liegt darin, dass die Entwicklung von Technologien aktuell durch den technologischen Fortschritt und weniger durch evidenzbasierte und evidenzorientierte Forschung vorangetrieben wird.In diesem Überblicksartikel wird das Feld „Digital Public Health“ konzeptuell beschrieben und anhand von grundlegenden Public-Health-Funktionen als Anforderungsprofil definiert. Wir diskutieren einige Beispiele, wie digitale Technologien aktuell zur Erfüllung von Public-Health-Aufgaben genutzt werden, und schlagen eine bedarfsorientierte Entwicklung von digitalen Gesundheitstechnologien vor.Wir gehen außerdem auf spezifische Herausforderungen, insbesondere sozioökonomische Unterschiede in der Nutzung und in den Effekten von digitalen Gesundheitstechnologien, sowie Datenschutz- und ethische Aspekte ein.

ObjectiveTo scope published data on the development, evaluation and implementation of digital health technologies for use in wound care. We focused on digital health technologies that supported one or more of the following functions: system level (such as electronic health records, management systems), wound imaging and measurement, and communication. MethodsFor this rapid scoping review, Ovid MEDLINE and Ovid Embase were searched in January 2021 and relevant experts were consulted. We identified English language publications that reported the development, evaluation, and/or implementation of relevant digital health technologies. Studies were screened and data extracted and coded following the established scoping review methodology. Data were presented narratively, and in tabular formats. ResultsWe included 156 studies in the review. After reported technologies were categorised based on their predominant function, 51 (32.7%) studies reported on system level technologies; 123 (78.8%) on wound imaging and measurement technologies; and 34 (21.8%) on communication-focused technologies such as video-conferencing technologies, messaging technologies). Of the 156 studies, 37 (23.7%) reported data on development of the technology; 135 (86.5%) reported evaluation activities, mainly for wound imaging and measurement technologies; and 2 (1.3%) reported implementation research. ConclusionThere is increasing focus on digital health technologies in wound care. Assessment of digital health technologies aimed at wound care has mainly been for those with a primary function around wound imaging and measurement. Most studies reported evaluation whilst evidence suggests the field may lack transparent reporting of technology development and implementation activities that could aid further decision-making.

Health Technology Assessment for Cardiovascular Digital Health Technologies and Artificial Intelligence: Why Is It Different?

Digital health technologies and health-care privatisation

IntroductionDigital health care is a rapidly growing and increasingly diverse area of medicine and social care. Health technology assessment (HTA) agencies around the world are engaging with digital health technologies and developing methods for appropriately assessing their value. Given our experience in HTA for pharmaceuticals and how methodologies must differ when assessing medical devices and diagnostics, we must be proactive in rapidly developing useful methods for assessing a variety of digital health technologies.MethodsWe will first present the results of two completed HTAs from the UK and contrast their methods and results, while looking at the UK approach to assessing digital health care in general. Next, we will present preliminary results from an ongoing consensus conference study of HTA’s for integrated digital technologies. This study will use a modified Delphi methodology to develop statements for discussion at a consensus conference. The primary research question is “how digital technologies can help build resilient healthcare systems and how HTAs can assess their value”.ResultsAn HTA conducted in the UK of an artificial intelligence-enabled ambulatory electrocardiogram device resulted in a recommendation for further real-world evidence generation. Another HTA of a digital therapeutic app for insomnia, which was also conducted in the UK, resulted in a positive recommendation but the process was lengthy and needed to be flexible. The preliminary results of an upcoming consensus conference study will also be presented. The consensus panel will consist of a range of stakeholders from digital experts, HTA practitioners, clinicians, health economists, industry representatives, and policy makers.ConclusionsDigital technology is now a broad field with a wide range of very different technologies included in its definition. Questions remain as to whether digital technologies should be assessed using a traditional pharma-based framework for HTA, a MedTech model, or something else entirely. Given our past experience of developing flexible methods for HTA, we have an opportunity to develop useful recommendations and best practices from the ground up.

Evaluating and integrating digital health technologies is a critical component of a national healthcare ecosystem in the 2020s and is expected to even increase in significance. The paper gives an overview of international practices on public financing and health technology assessment of digital health technologies (DHTs) in five European Union (EU) countries and outlines recommendations for country-level action that relevant stakeholders can consider in order to support uptake of digital health solutions in Hungary. A scoping review was carried out to identify and gather country-specific classifications and international practices on the financing DHTs in five pioneering EU countries: Germany, France, Belgium, the United Kingdom and Finland. Several frameworks have been developed for DHTs, however there is no single, unified framework or method for classification, evaluation, and financing of digital health technologies in European context. European countries apply different taxonomy, use different assessment domains and regulations for the reimbursement of DHTs. The Working Group of the Hungarian Health Economic Society recommends eight specific points for stakeholders, importantly taking active role in shaping common clinical evidence standards and technical quality criteria across in order for common standards to be developed in the European Union single market. Specificities of national healthcare contexts must be taken into account in decisions to allocate public funds to certain therapies rather than others.

Digital health technology provides opportunities to leverage artificial intelligence and other digital applications to promote cardiovascular health. Digital health technologies include artificial intelligence (such as machine learning [ML], neural networks),1 analytic systems, mobile apps, wearables, email, text messaging, and telemedicine.2 In this article, we review the role of digital technology in cardiovascular health and a selection of recent studies to evaluate the evidence of its effectiveness. Artificial intelligence is broadly defined as the capability of computer systems to perform tasks similar to humans.3 Examples include vision, speech, pattern recognition, and decision making. Machine learning is the ability of the computer program to learn from experience. This typically occurs from analysis of large sets of data processed through human-derived algorithms to enhance, predict, and explain outcomes.4 An example of the use of ML in clinical care is cardiovascular disease (CVD) prediction and electrocardiographic interpretation. Neural networks, named after the human nervous system, are nonlinear statistic models that control where signals are sent. Neural networks can be used for decision making such as cardiovascular diagnosis confirmation. Digital Technology Use in Cardiovascular Risk Assessment Several studies have demonstrated improved CVD risk factor identification using ML compared with traditional risk assessment tools. Researchers developed an ML risk calculator and compared it with the American College of Cardiology/American Heart Association CVD risk calculator in 6459 participants from the Multi-Ethnic Study of Atherosclerosis.5 Study participants were free of CVD at baseline and followed for 13 years. Results revealed that the American College of Cardiology/American Heart Association risk calculator was less precise: statin therapy was recommended to 46% of the sample, with 23.8% of CVD events occurring in those not recommended a statin. In comparison, the ML risk calculator recommended a statin to 11% of the sample, with 14.4% of CVD events occurring in those not recommended a statin.5 Similarly in 3 cohorts from Australia, 4 ML models were developed and compared with the 2008 Framingham model. The ML models provided 2.7% to 5.2% better predictions across all 3 cohorts.6 Taken together, the authors of these studies suggest ML provides promise in providing more precise estimates of CVD risk. Digital Health Interventions for Cardiovascular Disease Prevention Digital health interventions have the potential to provide a personalized approach to promote cardiovascular health. Behavior change theory is a key component of digital interventions and includes theoretical frameworks such as supportive accountability,7 self-efficacy theory,8 social cognitive theory, and the health belief model.9 Precision healthcare has been promoted for decades. Many of the challenges in operationalizing precision healthcare are healthcare accessibility, scheduling, care continuity, and inadequate knowledge exchange between provides and patients.10 Thus, promotion of healthy lifestyles and lifestyle risk factor reduction remain inadequately addressed in patients with CVD.11 To achieve sustainable change, individual-level personalized strategies may be leveraged through digital health interventions. Evidence of the effectiveness of digital health interventions has varied but is promising overall. Text messaging has been successfully used to provide information regarding healthy diet and physical activity recommendations, monitoring, and individual feedback. Text messaging has resulted in improvements in diet and activity in many (TextMe,12 Mobile MyPlate,13 MyQuest,14 Text-To-Move15), but not all studies.16 Smartphone/mobile apps have been designed to improve dietary and physical activity behavior. Examples include apps that track dietary patterns and activity through user input of text or visual images.17,18 Users can set their own goals and receive feedback on progress toward goals. Reviews of smartphone apps have had variable results with many demonstrating short-term improvement. Villinger et al19 conducted a systematic review and meta-analysis of the effectiveness of mobile app interventions on nutrition behaviors (41 studies, 27 randomized controlled trials [RCTs]). Findings revealed significantly improved nutrition behaviors and nutrition-related outcomes (P = .004 and P = .043, respectively). A second systematic review of 27, primarily RCTs, found significant between-group improvements in 19 of the 27 studies.20 A meta-analysis of 6 RCTs in adults using a smartphone app as the primary component of the intervention revealed a trend for more steps per day in the intervention compared with the control groups, with programs lasting less than 3 months more effective than longer programs.21 Taken together, text messaging and smartphone/mobile apps have the potential to improve lifestyle behaviors associated with cardiovascular health. The addition of strategies to increase sustainability of the effects needs to be assessed. Digital Health Interventions: Primary and Secondary Prevention Widmer et al2 conducted a meta-analysis of 51 RCTs and cohort studies using digital health interventions for the prevention of CVD events and risk factor modification. Subgroup analyses of primary prevention studies (2 studies) did not provide evidence of a statistically significant reduction in CVD outcomes. However, evaluation of individual risk factors in primary prevention studies found a significant reduction in weight (11 studies; −3.35 lb), systolic blood pressure (23 studies; mean difference, −2.12 mm Hg), total cholesterol (13 studies; mean difference, −5.19 mg/dL), low-density lipoprotein cholesterol (8 studies; mean difference, −4.96 mg/dL), and glucose (6 studies; mean difference, −1.38 mg/dL).2 A subgroup analysis of secondary prevention studies demonstrated a significant impact of digital interventions on CVD outcomes (relative risk, 0.60; a 40% relative risk reduction), improvement in body mass index (6 studies; mean difference, −0.31 kg/m2) but no improvement in weight, systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and glucose. Taken together, this meta-analysis suggested that digital interventions were beneficial not only in lowering CVD events in higher-risk patients but also in lowering risk factors in primary prevention approaches.2 In a second meta-analysis conducted by Akinosun et al,11 researchers analyzed 25 RCTs in patients with traditional CVD risk factors who received a digital intervention versus usual care.11 Findings revealed benefits in total cholesterol (mean difference, −0.29), high-density lipoprotein cholesterol (mean difference, −0.09), low-density lipoprotein (mean difference, 0.18), physical activity (mean difference 0.23), physical inactivity (relative risk, 0.54), and diet (relative risk, 0.79). There was no significant improvement in body mass index, systolic and diastolic blood pressure, hemoglobin A1C, alcohol intake, smoking, and medication adherence. Authors concluded that digital interventions were more effective at improving healthy behaviors than reducing unhealthy behaviors. In patients who experienced a myocardial infarction, a digital health intervention providing medication reminders, vital sign and activity tracking, education, and outpatient care coordination resulted in a 52% lower 30-day readmission rate compared with usual care.22 Sociodemographic characteristics (age, sex, and race) did not influence use of the digital intervention, highlighting a potential role for digital interventions in the promotion of equity in social determinants of health.23 Digital Health Interventions in Cardiac Rehabilitation Cardiac rehabilitation is an essential component of secondary prevention of CVD.24 Some patients face barriers in participation in cardiac rehabilitation due to physical accessibility, time, and travel.25 Digital health interventions have the potential to bridge these barriers and increase participation. Digital delivery of cardiac rehabilitation therapy with real-time personalized support has several advantages.26 In a systematic review of 31 studies in which authors examined digital health interventions for cardiac rehabilitation, the results revealed that cardiac rehabilitation program adherence was greater in patients using digital interventions than traditional methods alone. Secondary benefits were found in self-efficacy, weight management, diet, and quality of life. Taken together, digital cardiac rehabilitation was feasible and effective whether used alone or in combination with traditional cardiac rehabilitation.26 Conclusion Digital health technology is an evolving field with tremendous potential to improve cardiovascular health. Cardiovascular disease remains the major cause of death in the United States. The age-adjusted mortality rate has increased in the last decade. More people died from CVD causes in 2020 (nearly 900 000 deaths) than any year since 2003.27 Opportunities to reduce CVD and CVD risk have not been fully leveraged, and digital technology interventions have the potential to meet this need. Digital health technology also has the potential to provide equitable and personalized care. Device data, electronic medical record data, and social determinants of health data provide an opportunity to combine and identify longitudinal trends and risk factors before CVD begins. In the future, large data sets can be created that can be analyzed using ML to identify patterns and structures within and among the data to provide a more robust risk assessment to promote CVD prevention.

Being a 21st-century health care provider is extremely demanding. The growing number of chronic diseases, lack of medical workforce, increasing amounts of administrative tasks, the cost of medical treatment, and rising life expectancy result in an immense challenge for medical professionals. This transformation has been triggered by the growing presence of digital health. Digital health does not only refer to technological transformation; it also fundamentally reshapes the physician-patient relationship and treatment circumstances. We argue that patient empowerment, the spread of digital health, the biopsychosocial-digital approach, and the disappearance of the ivory tower of medicine lead to a new role for physicians. Digital health allows the job of being a medical professional to become more rewarding and creative. The characteristics of a physician-as-idol could shift from self-confident to curious, from rule follower to creative, and from lone hero to team worker. Empowered physicians (e-physicians) can be described as “electronic,” where they use digital technologies in their practice with ease; “enabled,” where they are enabled by regulations and guidelines; and “empowered,” where they are empowered by technologies that support their job and their empowered patients (e-patients). They can be described as “experts” in the use of technologies in their practice or in knowing the best, most reliable, and trustworthy digital health sources and technologies. They can also be described as “engaged,” when understanding the feelings and points of view of their patients, giving relevant feedback, and involving them throughout the whole healing process. The skills and approaches that characterize this era of e-physicians, such as face-to-face communication skills, digital literacy, interdisciplinarity, knowing where to find information, translating large amounts of data into insights for patients, among others, should always have been at the core of practicing medicine. However, the economical, technological, and administrative burden of the profession has not made it possible for most physicians to enjoy the benefits of their training, individual capabilities, and creativity. By understanding how digital health technologies can support or augment their capabilities, physicians would have the chance to practice the art of medicine like never before.

Digital health technologies can potentially reduce health disparities in cancer care. However, the benefits of digital health technology depend partly on users' digital health literacy, that is, "capabilities and resources required for individuals to use and benefit from digital health resources," which combines health and digital literacy. We examined issues for digital health technology implementation in cancer care regarding digital health literacy, via stakeholder consultation. Consumers, health care professionals, researchers, developers, nongovernment and government/policy stakeholders (N=51) participated in focus groups/interviews discussing barriers, enablers, needs and opportunities for digital health implementation in cancer care. Researchers applied framework analysis to identify themes of digital health literacy in the context of disparity and inclusion. Limited digital and traditional health literacy were identified as barriers to digital technology engagement, with a range of difficulties identified for older, younger and socio-economically or geographically disadvantaged groups. Digital health technology was a potential enabler of health care access and literacy, affording opportunities to increase reach and engagement. Education combined with targeted design and implementation were identified means of addressing health and digital literacy to effectively implement digital health in cancer care. Implementing digital health in cancer care must address the variability of digital health literacy in recipients, including groups living with disadvantage and older and younger people, in order to be effective. SO WHAT?: If cancer outcome disparity is to be reduced via digital health technologies, they must be implemented strategically to address digital health literacy needs. Health policy should reflect this approach.

Digital health technologies can potentially increase the efficiency and quality of pediatric palliative care (PPC), yet their use in home-based PPC remains limited. Limited digital health care literacy and inadequate training can reduce confidence and foster negative attitudes, whereas positive experiences and basic digital health care literacy may encourage adoption. This study aims to explore the use of digital health technologies by Norwegian health care personnel in home-based PPC and examine the association between their digital health care literacy and their attitudes toward digital health. A cross-sectional study was conducted from September 2023 to May 2024, with an online survey targeting health care personnel involved in home-based PPC through primary or specialist health care services. Data were collected using selected items from the Norwegian Healthcare Personnel Survey on eHealth 2022, the Digital Health Care Literacy Scale (DHLS), and the Information Technology Attitude Scales for Health (ITASH), alongside demographic characteristics. Higher DHLS scores indicate greater digital health care literacy, while higher ITASH scores reflect more positive attitudes toward digital health technologies. Pearson correlation, ANOVA, and multiple linear regression analyses were conducted to comprehensively explore the relationships and associations among the variables. Health care personnel (n=148) from diverse health care services responded to the survey. Half of the respondents (72/144, 50%) had experience with real-time video consultation, while phone calls were the primary communication method (138/145, 95.2%). Additionally, 55.6% (79/142) of the respondents had limited or minimal access to electronic health records from other health care services. Health care personnel perceived digital health technologies for remote PPC as a supplement (126/135, 93.3%) rather than a replacement for in-person care. Mean digital health care literacy was 18.29 (SD 3.8) on a scale from 0 to 23. On a scale from 1 to 4, the highest recorded scores pertained to attitudes toward digital health technologies in supporting care (mean 3.17, SD 0.39) and the perceived need for training (mean 3.16, SD 0.43). A statistically significant association was found between the respondents' level of digital health care literacy and their attitudes toward digital health technologies in supporting care (β=0.030, 95% CI 0.014-0.047; P<.001). This study examined the use of digital health technologies by Norwegian health care personnel in home-based PPC, their digital health care literacy, and attitudes toward digital health. Despite positive attitudes and high digital health care literacy, use of digital health technologies was limited, suggesting that inadequate digital health solutions may hinder effective implementation. Addressing these barriers is crucial to enhancing the implementation of digital health in home-based PPC. Future research should focus on integrating digital health technologies into existing infrastructure and workflows while exploring their impact on personalized care to ensure high-quality home-based PPC.

Digital health education and an understanding of effective technology application are essential for shaping the clinical environments of the future. This requires an understanding of nursing students’ attitudes and behaviours in health education. The objective of this study was to investigate nursing students’ perceptions of and attitudes towards digital health technologies. The study employed a qualitative research method focusing on the independent work of the students enrolled in the 2023/2024 Digital Technologies in Health course. Qualitative data were collected through Moodle, the common e-learning platform at Tallinn Health University of Applied Sciences. The document analysis database consisted of 185 student self-reflections and self-assessments. Trust in technology and the use of software emerged as key factors in the learning process. Students recognised the importance of quality health data and demonstrated trust in utilising electronic records, even when lacking previous experience. Despite their positive attitudes towards digital technologies, significant challenges remain in the application of fundamental digital skills. The most pressing concerns are related to digital literacy and innovation. Students perceive the use of digital tools as potentially distancing healthcare professionals from patients, which raises ethical concerns, particularly in relation to their future professional roles. Nursing educators should prioritise fostering a strong professional nursing identity, with particular emphasis on the positive impact of digital health technologies in clinical practice.